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Audio Signal Processing Engineer

vor 2 Monaten


Renningen, Baden-Württemberg, Deutschland Bosch Vollzeit
Job Description

**Targeted Speech Understanding in Multi-Source Auditory Environments**

In today's hearing acoustics applications, such as ear buds, hearing aids, smart watches, and in-car acoustics, targeted speech understanding is crucial for delivering exceptional user experiences. To address this challenge, AI-based systems, including recurrent neural networks, LSTMs, and beamformer networks, are being deployed to perform noise cancellation and speaker enhancement.

**Investigating Target Speech Extraction with Directives**

In this Master thesis, you will investigate target speech extraction with different background noises and develop a target extraction method based on directives. You will evaluate speech extraction methods for hearing aids, focusing on their performance in various auditory environments.

Key Responsibilities:

  • Develop and implement a target extraction method based on directives
  • Evaluate speech extraction methods for hearing aids in various auditory environments
  • Perform data augmentation on toy datasets and implement pre-processing stages of audio
  • Develop neural networks to extract target speech based on directives
  • Extend the developed method to multi-source speech targets
  • Collaborate with a cross-functional team spanning algorithms, deployment, and hardware

Requirements:

  • Master studies in Electrical Engineering, Computer Science, or a comparable field
  • Experience and knowledge in Python and C++; background in Neural Networks; knowledge of PyTorch is an advantage
  • Independent, structured, and highly motivated individual
  • Keen interest in future technologies and trends with a passion for innovation
  • Fluent in English; German is an advantage

Additional Information:

This thesis requires enrollment at a university. Please attach your CV, transcript of records, examination regulations, and if indicated, a valid work and residence permit.

Bosch values diversity and inclusion and welcomes all applications, regardless of gender, age, disability, religion, ethnic origin, or sexual identity.